The current overarching office themes include accelerating scientific discovery, exploring fundamental limits, and expecting the unexpected. In support of this mission, the DSO Office-wide BAA invites proposers to submit innovative basic or applied research concepts in one or more of the following technical areas: Mathematics, Modeling and Design; Physical Systems; Human-Machine Systems; and Social Systems.

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The Defense Sciences Office at the Defense Advanced Research Projects Agency (DARPA) is soliciting innovative research proposals in the area of new simulation capabilities to test the accuracy and robustness of causal modeling methods for understanding human social systems and behaviors.

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This award is to design, code, document, test, dissememinate, and maintain Stan, an extensible open-source software framework and compiler for efficient and scalable Bayesian statistical modeling. Stan is an extensible, open-source, cross-platform software framework for developing Bayesian statistical models. The first step in Bayesian modeling is setting up a full probability model for all quantities of interest. Stan facilitates this process by providing an expressive and extensible domain-specific programming language for specifying probabilistic models.

How does the understanding of social networks contribute to social science? In particular, (1) which network features or observable characteristics encode social structure; (2) how do these features contribute to the formation of connections or social ties; and (3) how does network structure impacts diffusion, specifically the spread of influences, opinions, and diseases? A key difficulty in studying these questions is that most contributions to current understanding in this area come from a small number of applications where full network data are readily available.